{"id":"W1968877095","doi":"10.1177/0957650912460182","title":"Investigation of a hybrid renewable– microgeneration energy system for power and thermal generation with reduced emissions","year":2012,"lang":"en","type":"article","venue":"Proceedings of the Institution of Mechanical Engineers Part A Journal of Power and Energy","topic":"Advanced Thermodynamic Systems and Engines","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Cogeneration; Renewable energy; Stirling engine; Natural gas; Environmental science; Hybrid system; Greenhouse gas; Process engineering; Fossil fuel; Automotive engineering; Thermal; Waste management; Electricity generation; Environmental engineering; Engineering; Power (physics); Computer science; Mechanical engineering; Electrical engineering; Meteorology; Thermodynamics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002481137,0.0002883193,0.0003410638,0.0002740329,0.0005929086,0.0007161297,0.000549331,0.000372715,0.002378965],"category_scores_gemma":[0.0002003866,0.0001931947,0.0003118674,0.0003302975,0.0003462031,0.000480081,0.0003372152,0.0002446698,0.0002077622],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008682184,"about_ca_system_score_gemma":0.0008369508,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01086624,"about_ca_topic_score_gemma":0.02418238,"domain_scores_codex":[0.9998883,0.00002605465,0.000004651595,0.00001867842,0.00004173858,0.00002052842],"domain_scores_gemma":[0.9999248,0.00002328128,0.000006633197,0.000009572394,0.00002469729,0.00001095878],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00119936,0.0006469699,0.007230883,0.000537906,0.0001696671,0.001296022,0.000248324,0.7891426,0.1304017,0.007704454,0.0009319428,0.06049019],"study_design_scores_gemma":[0.0003826165,0.002233225,0.00972667,0.00002454212,0.0001478017,0.0003447572,0.0003964031,0.924754,0.05148176,0.002188063,0.008272496,0.00004765739],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9652242,0.0002175826,0.02301958,0.0001028413,0.00002238298,0.0001802213,0.0001254536,0.0001833328,0.01092437],"genre_scores_gemma":[0.9931591,0.00005645476,0.005421928,0.000008428617,0.000001725786,0.00002928471,0.00004768611,0.000005990125,0.00126945],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01086624,"threshold_uncertainty_score":0.02160597,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009841504557330863,"score_gpt":0.1873597197683576,"score_spread":0.1775182152110267,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}